The so-named Internet-of-Things (IoT) can be generally described as the inter-networking of assets (e.g., physical devices, vehicles, buildings, and other items) that are embedded with electronics, software, sensors, actuators, and network connectivity to enable the assets to collect and exchange data. Such interconnected assets are commonly referred to as connected devices, and/or smart devices.
As IoT systems evolve, connected devices are expected to perform more and more intelligence at the local-level. It is envisioned that, for example, as artificial intelligence (AI) and IoT technologies develop, individual IoT devices can initiate interactions for service discovery and service composition, without human intervention. For example, a smart watch could request wireless charging services without bothering the user, when there are one or more wireless chargers available in the ambient environment. To achieve this, the IoT device would select a target device (agent). Selection of a target device, however, should be based on the agent's trustworthiness. A trust management system can play a critical role in this aspect.
In traditional IoT paradigms, trust management systems do not include an intelligent means of boot-strapping a priori trust. Instead, trust management systems use either a fixed and intuitive number to evaluate the a priori trust of an agent (e.g., zero (0) for no trust, and 0.5 for a trust attitude of ignorance). However, such fixed values often do not accurately represent the eventual deserving trust value (ground truth) of the agent. Moreover, this boot-strapped a priori trust value is of great significance in the decision making for the first few interactions towards the agent, and is particularly important in the IoT ecosystems where agents usually form ephemeral ad hoc interactions.